As the Internet continues to exponentially expand, the role of search engines has dramatically increased. The sheer volume of data has quickly become impossible for a human user to manipulate on his or her own. Thus, the use of search engine technology has become a vital tool in the useful operation of the Internet.
Great strides have been made in optimizing search engines with respect to the quality of results returned in response to a query. Currently existing algorithms allow users to usually identify relevant websites within seconds of submitting a query. However, despite these advances very little advances have been made with respect to analyzing specific or aggregate user behavior and providing easily accessible data to the user directly on the SRP.
As an example, the current state of the art fails to capitalize on semantic data present within search engine results pages. Currently, many websites, including nearly all of the most frequently trafficked sites, contain semantic data such as RDF/XML, N3, etc. data that can be extracted and parsed into an easily accessible format for an end user. Additionally, many common search queries may be satisfied not by websites but by simple applications or widgets provided directly to the user. Thus, there currently exists a need for intelligent, user-centric search results pages.